Investing in Global Equity Markets with Particular Emphasis on Chinese Stocks

Guerard, John B.; Deng, Shijie; Gillam, Robert A.; Markowitz, Harry M.; Xu, Ganlin; Wang, Ziwei

doi:10.2139/ssrn.2744304

Cited by 2 publications

(3 citation statements)

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“…We use data only as it is known (or more exactly, our portfolios are tested out-of-sample). 6 [30] and Guerard et al [31].…”

Section: A Review Fundamental Variables and Regression-based Expectedmentioning

confidence: 96%

“…The Axioma Statistical Risk Model, World-Wide Equity Risk Factor Model, AX-WW2.1, estimates 15 principal components to measure risk. See Guerard et al [31] for a comparison of Axioma Fundamental and statistically based risk models. Guerard et al [31] reported that the statistical model dominated the fundamental risk model in producing a higher set of returns for a given level of risk.…”

Section: Constructing Mean-variance Efficient Portfoliosmentioning

confidence: 99%

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A Case Study of Forecasted Earnings Acceleration and Stock Selection in Global and Emerging Stock Markets

Guerard

Saxena

2018

Front. Appl. Math. Stat.

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The allocation of scarce economic resources so as to maximize societal good is at the very core of human economic development. The key contribution of Markowitz [1] was to view this age-old activity in a scientifically rigorous manner, and bring three key elements to the forefront, namely, risk, return and correlations. Since the publication of Markowitz' seminal paper, investment professionals have expensed significant resources in identifying, understanding, and monetizing new sources of uncorrelated returns. This paper moves forward that narrative by focusing on Emerging Markets (EM) and demonstrating the effectiveness of earnings acceleration factors in building significantly better mean-variance optimized portfolios.

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“…We use data only as it is known (or more exactly, our portfolios are tested out-of-sample). 6 [30] and Guerard et al [31].…”

Section: A Review Fundamental Variables and Regression-based Expectedmentioning

confidence: 96%

Section: Constructing Mean-variance Efficient Portfoliosmentioning

confidence: 99%

A Case Study of Forecasted Earnings Acceleration and Stock Selection in Global and Emerging Stock Markets

Guerard

Saxena

2018

Front. Appl. Math. Stat.

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“…This is the main reason for using MQ as one of the fundamental variables in this study. Compared to REG10, CTEF, and PM, there have been fewer studies on the efficiency of the MQ variable in stock selection: Guerard et al [18] found the MQ variable produces statistically significant returns in the vast majority of the eight universes: the Russell 3000, MSCI All Country World, MSCI ex-US, MSCI Emerging Markets, MSCI Japan, MSCI China, a broader China universe and a two-analyst I/B/E/S global universe. Shao [8] showed that the Mean-ETL portfolio of the U.S. stocks based on the MQ variable outperforms the portfolio based on the USER and PM variables with highly statistically significant active returns.…”

Section: Mckinley Capital Quant Score (Mq)mentioning

confidence: 99%

Mean-ETL Optimization in HorseRace Competition

Shao¹

2018

Front. Appl. Math. Stat.

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In this paper, we present the methodology and results of the portfolios submitted to the HorseRace competition. The nine portfolios were constructed by applying the Mean-ETL optimization approach. The Mean-ETL optimization approach uses three fundamental variables (CTEF, MQ, and REG10) and three stock universes (GL, XUS, and EM), with each of the three fundamental variables applied one at a time to one of the three universes. This study assesses the return of the nine portfolios, and we report that all of these Mean-ETL portfolios produce positive active returns and most of them are statistically significant. Additionally, MQ variable is found to be the best among these three variables in the Mean-ETL portfolio construction.

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Investing in Global Equity Markets with Particular Emphasis on Chinese Stocks

Cited by 2 publications

References 0 publications

A Case Study of Forecasted Earnings Acceleration and Stock Selection in Global and Emerging Stock Markets

A Case Study of Forecasted Earnings Acceleration and Stock Selection in Global and Emerging Stock Markets

Mean-ETL Optimization in HorseRace Competition

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